Unravelling the genetic basis of hereditary disorders by high-throughput exome sequencing strategies

Jazayeri, O., 2016, [Groningen]: University of Groningen. 182 p.

Research output: ThesisThesis fully internal (DIV)

Copy link to clipboard


  • Title and contents

    Final publisher's version, 345 KB, PDF document

  • Chapter 1

    Final publisher's version, 595 KB, PDF document

  • Chapter 2

    Final publisher's version, 1.39 MB, PDF document

  • Chapter 3

    Final publisher's version, 1.62 MB, PDF document

  • Chapter 4

    Final publisher's version, 897 KB, PDF document

  • Chapter 5

    Final publisher's version, 4.57 MB, PDF document

  • Chapter 6

    Final publisher's version, 483 KB, PDF document

  • Appendices

    Final publisher's version, 306 KB, PDF document

  • Complete thesis

    Final publisher's version, 7.77 MB, PDF document

  • Propositions

    Final publisher's version, 62.6 KB, PDF document

  • Omid Jazayeri
The research presented in this thesis focuses on using Whole Exome Sequencing (WES) to unravel the genetic basis of human hereditary disorders with different inheritance patterns. We set out to apply WES as a diagnostic approach for establishing a molecular diagnosis in a highly heterogeneous group of patients with microcephaly and varied intellectual disability. Additionally, a family with familial glucocorticoid deficiency (FGD) and a cohort of patients with L1 syndrome were studied.
In our microcephaly project, we achieved a diagnostic yield of 29% and found mutations in known disease-genes. Our results confirmed that many microcephaly cases are explained by autosomal recessive inheritance. For FGD, trio-exome sequencing revealed a novel homozygous mutation in the NNT gene. We also reviewed the literature for all reported NNT mutations and their clinical presentation. By application of X-exome sequencing in a cohort of 58 patients with L1 syndrome, an X-linked disorder, we identified 5 possible novel candidate genes, among which three independent mutations in DACH2 suggest this gene as the most promising candidate gene for L1 syndrome. Finally, using an in silico composite biological network analysis, we identified molecular pathomechanisms underlying congenital microcephaly (CM) and predicted further CM-candidate genes. Next to known processes, our analysis suggested, telomere biology and tRNA metabolic process as biological functions underlying CM. Supportive evidence for several selected candidate genes demonstrated the potential of our network approach to facilitate gene discovery in genetically heterogeneous disease.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
Award date20-Jun-2016
Place of Publication[Groningen]
Print ISBNs978-90-367-8972-1
Electronic ISBNs978-90-367-8971-4
Publication statusPublished - 2016

Download statistics

No data available

ID: 32974071